Patterns before recognition: the historical ascendance of an extractive empiricism of forms

Abstract

AbstractThis article explores the complex convergence between cybernetics and Gestalt theory and its influence on the concept of pattern recognition. It finds a departure in the analogous ways each discipline extends their core frameworks toward social and anthropological objects. However, this shared ground is not without tensions. In the post-war American context, what is formalizable and realizable in mechanical structures has a certain explanatory authority—even if often misplaced-- concerning perception and human intelligence. Cultural patterns feed into mechanical recognition of patterns, exemplifying “extractive empiricism” or the process of outsourcing experiential processes to mechanical systems. This mode of “proof” is also evident in cybernetic and cognitive psychological strategies toward Gestalt theory, leaving a significant legacy for contemporary machine learning approaches. By examining the early interactions between these rival paradigms, known for their quest for generalization, and disentangling their source status, this inquiry contributes to understanding the broad conceptual possibilities of pattern recognition beyond its narrow confines in engineering perspectives and machine learning discourse.